Smart Gloves Development implementing TinyML for Real-time Sign Language Recognition
| dc.contributor.author | DEEPAK KUMAR SHAW : RITIKA BASAVARAJ HIREMATH : VANSHIKA SAI RAMADURGAM | |
| dc.date.accessioned | 2024-11-05T05:37:21Z | |
| dc.date.available | 2024-11-05T05:37:21Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Communication is a major part of our daily life. For people who are deaf and dumb, sign language is imperative. A Sign language contains various hand movements and finger placements which in turn form different gestures. Learning any sign language can be challenging. With the current number of different sign languages available around the world, it makes it very hard for people to use sign languages for communication without the help of a translator. The need for a translator every time while conversing with a person makes their communication speed slower. In addition, with the current availability of over 300 sign languages, it is highly impossible for two people to know the same sign language for communication. The aim of this project is to develop smart gloves with TinyML implementation to provide better means of sign language recognition and help a hearing or speech-impaired person to communicate without any inhibitions by giving accurate results. The smart gloves are developed for American Sign Language (ASL) recognition using TinyML on an Arduino Uno microcontroller board and flex sensors. | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/16070 | |
| dc.language.iso | en | |
| dc.publisher | NHCE | |
| dc.title | Smart Gloves Development implementing TinyML for Real-time Sign Language Recognition | |
| dc.type | Learning Object |